| import os |
| from datetime import datetime |
|
|
| from gradio_client import Client |
|
|
|
|
| def save_images(images, used_seeds, output_dir="outputs"): |
| os.makedirs(output_dir, exist_ok=True) |
| timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") |
|
|
| for index, image in enumerate(images): |
| filename = f"{timestamp}_img{index + 1}.png" |
| path = os.path.join(output_dir, filename) |
|
|
| |
| if hasattr(image, "save"): |
| image.save(path) |
| else: |
| from PIL import Image |
|
|
| Image.open(image).save(path) |
|
|
| print(f"Saved: {path}") |
|
|
| print(f"Seeds used: {used_seeds}") |
|
|
|
|
| def main(): |
| |
| space_id = "yingzhac/Z_image_NSFW" |
|
|
| client = Client(space_id) |
|
|
| prompt = "A beautiful portrait photo of a woman, 4k, highly detailed" |
| negative_prompt = "" |
| height = 1024 |
| width = 1024 |
| num_inference_steps = 9 |
| guidance_scale = 0.0 |
| seed = 42 |
| randomize_seed = False |
|
|
| images, used_seeds = client.predict( |
| prompt, |
| negative_prompt, |
| height, |
| width, |
| num_inference_steps, |
| guidance_scale, |
| seed, |
| randomize_seed, |
| api_name="/generate_image", |
| ) |
|
|
| save_images(images, used_seeds) |
|
|
|
|
| if __name__ == "__main__": |
| main() |